• Journal of the Korean Home Economics Association
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• v.29 no.2
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• pp.155-167
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• 1991

There have been many cooperative meetings from the past in our country. "Kye" is the most popular and current exisiting meeting of them in our society. Therefore, study of "Kye" at this point will be useful for life, attitude, value in urban area. The concret purposes of this study are to investigate: (1) Participationg rate of the city housewives' "Key" meeting. (2) Purpose of the city housewives' "Kye" meeting. (3) The order of the most influential variable among the socio-economic variables, the family life cycle variables, and the residence variables on the city housewives' "Kye" meeting. For the purpose of this main study, 600 questionnaires were distributed to housewives living in Seoul and collected during the six months, from November, 1989 to April, 1990. And method of data analysis for this survey was Multiple Regression. The major results are as follows: (1) Participating rate of city housewives' "Kye" meeting is 52.2%. (2) Purpose of city housewives' "Kye" meeting is in the order of "for saving", "for friendly gatherings", "for commodity purchase". The order of the most influential factor (3) among the socio-economic variables is the age of respondents (β:.187), the average income of all house members(β:.177), and the schooling years (β:-.147), (4) among the family life cycle variables is the family life cycle(β:.261), number of children(β:-.212), (5) among the residence variables is the duration of current residence(β:.221), kind of house(β:.118). Comparing the past studies, the purpose of "Key" meetings has changed from the family centered events method such as worship or marriage of family members to out of the family and friends centered events such as social gatherings among the people in urban community.

• Journal of the Korean Institute of Landscape Architecture
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• v.30 no.6
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• pp.57-65
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• 2003

This study researches attributes , behaviors , satisfaction factors and degrees of curiosity of visitors to recreational forests in the suburbs of a large city. It aims to present suggestions for urban forest development and management policy by offering basic data which help to plan, design and manage recreational forests to increase the quality of these environments. The results are as follows First, in attribute, the visiting rate of males is higher than that of females, and the main users are in their thirties and forties. Sixty percent of visitors graduated from university and their rate of employment is evenly distributed. 95 percent of visitors are residents of the metropolitan area. In terms of behavior, major visitors are family units visiting during summer seasons and for overnight stays. 75% are re-visitors. 85% of visitors came to escape the city with families and friends, keep in good health and experience nature. Second, to extract the factors affecting visitor satisfaction in recreational forests, the natural environment, facilities, and management/use systems were identified as independent variables, while subordinate satisfactions were dependent variables. so regression analysis was used. Thus, the variables affecting the natural environment are quality of water, stream use, biodiversity, fresh air and landscape factors. The variables affecting facilities are puking, convenience, play facilities, sanitary arrangement and camping. Most important among the variables affecting management/use systems are educational facilities and access condition. On the basis of generalizing the study in the existing individual site, we must verify the visiting characteristics in recreational forests in the suburbs of a large city. Since development of recreational forests is understood as a sequence considering a site and a given condition, and since management and improvement must unfold according to these characteristics, a strategy is needed to reveal visitors' opinions about the site. Depending on the facilities and service, satisfaction of recreational forests is generally influenced by social and economic qualities. Also, this study can look into the effect according to use pattern motive and season. As suburban recreational forests have many overnight-users and younger men, programs suitable for these groups are needed. On the basis of variables affecting satisfaction according to natural environment, facilities, and use system, policies which can manage the natural environment and introduce educational programs are needed.

• Journal of the Korean Data and Information Science Society
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• v.20 no.1
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• pp.179-190
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• 2009

In the financial industry, the decision tree algorithm has been widely used for classification analysis. In this case one of the major difficulties is that there are so many explanatory variables to be considered for modeling. So we do need to find effective method for reducing the number of explanatory variables under condition that the modeling results are not affected seriously. In this research, we try to compare the various variable reducing methods and to find the best method based on the modeling accuracy for the tree algorithm. We applied the methods on the pension insurance of a insurance company for getting empirical results. As a result, we found that selecting variables by using the sensitivity analysis of neural network method is the most effective method for reducing the number of variables while keeping the accuracy.

• The Mathematical Education
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• v.50 no.2
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• pp.213-231
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• 2011

The purpose of this study is to analyze the 6th graders' understanding of the concepts of variable on various aspects of school algebra. For this purpose, the test of concepts of variable targeting a sixth-grade class was conducted and then two students were selected for in-depth interview. The level of mathematics achievement of the two students was not significantly different but there were differences between them in terms of understanding about the concepts of variable. The results obtained in this study are as follows: First, the students had little basic understanding of the variables and they had many cognitive difficulties with respect to the variables. Second, the students were familiar with only the symbol '${\Box}$' not the other letters nor symbols. Third, students comprehended the variable as generalizers imperfectly. Fourth, the students' skill of operations between letters was below expectations and there was the student who omitted the mathematical sign in letter expressions including the mathematical sign such as x+3. Fifth, the students lacked the ability to reason the patterns inductively and symbolize them using variables. Sixth, in connection with the variables in functional relationships, the students were more familiar with the potential and discrete variation than practical and continuous variation. On the basis of the results, this study gives several implications related to the early algebra education, especially the teaching methods of variables.

• The Korean Journal of Applied Statistics
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• v.35 no.6
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• pp.739-754
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• 2022

Usually, text data consists of many variables, and some of them are closely correlated. Such multi-collinearity often results in inefficient or inaccurate statistical analysis. For supervised learning, one can select features by examining the relationship between target variables and explanatory variables. On the other hand, for unsupervised learning, since target variables are absent, one cannot use such a feature selection procedure as in supervised learning. In this study, we propose a word selection procedure that employs topic models to find latent topics. We substitute topics for the target variables and select terms which show high relevance for each topic. Applying the procedure to real data, we found that the proposed word selection procedure can give clear topic interpretation by removing high-frequency words prevalent in various topics. In addition, we observed that, by applying the selected variables to the classifiers such as naïve Bayes classifiers and support vector machines, the proposed feature selection procedure gives results comparable to those obtained by using class label information.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.15-22
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• 2023

An Ant Colony Optimization Algorithm(ACO) is one of the frequently used algorithms to solve the Traveling Salesman Problem(TSP). Since the ACO searches for the optimal value by updating the pheromone, it is difficult to consider the distance between the nodes and other variables other than the amount of the pheromone. In this study, fuzzy logic is added to ACO, which can help in making decision with multiple variables. The improved algorithm improves computation complexity and increases computation time when other variables besides distance and pheromone are added. Therefore, using the algorithm improved by the fuzzy logic, it is possible to solve TSP with many variables accurately and quickly. Existing ACO have been applied only to pheromone as a criterion for decision making, and other variables are excluded. However, when applying the fuzzy logic, it is possible to apply the algorithm to various situations because it is easy to judge which way is safe and fast by not only searching for the road but also adding other variables such as accident risk and road congestion. Adding a variable to an existing algorithm, it takes a long time to calculate each corresponding variable. However, when the improved algorithm is used, the result of calculating the fuzzy logic reduces the computation time to obtain the optimum value.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.4
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• pp.1-21
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• 2001

The purpose of this stuffy is to derive critical success factors for ERP system implementation by integrating managerial, technical. human resource and organizational culture factors welch have been proposed as influencing factors for the performance of ERP system implementation in previous studios. Especially, this stuffy divides ERP system implementation process into preparation stave, implement stage and settle-down and stabilization stave, and then derives critical success factors in each stage. The data for empirical analysis of the research model are collected from 64 companies and the respondents for questionnaire consist of ERP system implementation project managers and user department managers in companies which have already operated it after ERP system installation. The main results of this study are as follows. First, it derives 27 success factors through comprehensive review of various factors which may affect ERP system implementation performance, and categorizes them into one of three stapes preparation stave, implement stage, and settle-down and stabilization stage. Second, the relationship between many success factors at each stave (preparation stave, implement stage, and settle-down and stabilization stave) and performance variables is tested. As a result, the significant correlations between many success factors at each stage and ERP system implementation performance are found, and the difference among success factors in the degree of influencing the system performance is significantly shown. finally, the relationship between process-oriented performance variables and result-oriented performance ones is tested. As a result, it is found that there is significant correlation between process-oriented performance variables except for one variable-project resource management appropriateness - and result-oriented performance ones. The theoretical contribution of this study is to derive a comprehensive model of critical success factors for implementing ERP system project from the system deve1opment life cycle perspective, and empirically test it through field survey with a wide range of data collection. And, the practical implication of this study is to present the desirable guidelines for performing ERP system implementation project successfully.

• The Korean Journal of Applied Statistics
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• v.19 no.1
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• pp.149-161
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• 2006

The most important component in decision tree algorithm is the rule for split variable selection. Many earlier algorithms such as CART and C4.5 use greedy search algorithm for variable selection. Recently, many methods were developed to cope with the weakness of greedy search algorithm. Most algorithms have different selection criteria depending on the type of variables: continuous or nominal. However, ordinal type variables are usually treated as continuous ones. This approach did not cause any trouble for the methods using greedy search algorithm. However, it may cause problems for the newer algorithms because they use statistical methods valid for continuous or nominal types only. In this paper, we propose a ordinal variable selection method that uses Cramer-von Mises testing procedure. We performed comparisons among CART, C4.5, QUEST, CRUISE, and the new method. It was shown that the new method has a good variable selection power for ordinal type variables.

• The Journal of Information Systems
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• v.13 no.2
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• pp.22-48
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• 2004

Information systems that are not used cannot be useful. In order to increase user acceptance, it is necessary to understand why people accept or reject information systems. Technology Acceptance Model(TAM) is one of the most influential research models for studying determinants how users accept information systems. Recently, Knowledge Management Systems(KMS) have become important components of corporate systems as the foundation of industrialized economics has shifted from natural resources to knowledge assets. This paper applies TAM to investigate users' acceptance of KMS in public administration institutions. It sampled 182 users who had experience in using KMS. Many empirical researches have suggested that TAM can be integrated with other organizational theories to improve its predictive and explanatory ower. We extended the basic TAM by the integration of appraisal and reward satisfaction theory. There are many external variables that influence the perception and the belief of system users. We introduced two external variables(job characteristics, IT self-efficacy) and one additional perception variable, perceived appraisal and reward(PAR) in the basic TAM model. The LISREL model analysis is used for finding out the causality among variables and testing the model fitness. As result, The IT self-efficacy influences to the perceived ease of use(PEOU) and the PAR, and the PEOU influences directly to the perceived usefulness(PU), the PAR, and the attitude toward KMS. The KMS participation intention(PI) was influenced by the PAR and the attitude directly,andbythePEOUindirectly. Finally, this paper suggests some guidelines for the adoption of KMS in public sectors on the basis of the study results.

• Korean Journal of Adult Nursing
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• v.22 no.3
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• pp.260-270
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• 2010

Purpose: The main question is systematic review of the published in Korea and foreign countries on warming therapy for surgical patients. Methods: The researchers searched at Medline, CINAHL, KERIS, Adult Nursing Association, Korean Society of Nursing Science, Korean Academy of fundamentals of Nursing, and National Assembly Library web site for the published on warming therapy for surgical patients from 1980 to 2008. Words for search were operation/surgery, warming, operation/surgery and warming. Studies were included randomized controlled trial, and there were no restrictions regarding operative phase and outcome measures. Results: 36 published researches that met the criteria were mostly published in foreign countries between 2000 and 2008 and focused on surgery with general anesthesia. Sample size ranged from 21 to 60 subjects, age range between 21 and 60 years of age. Thirty different warming therapies were reported, fifty-two different dependent variables. Outcome indicators included active external warming, intra-operative, and body temperature. 'Positive effects' and 'no effects' equaled. The most frequently reported 'positive effects' were body temperature, shivering, and acid-base balance. No effects were more likely to be heart rate, blood pressure, and hemodynamics. Conclusion: Many types of warming therapy, are reported in the literature with little information about the efficacy of each, many different dependant variables were studied. There were no consistent reports as to length of time used for warming procedures. Overall, the effects of warming therapy are inconsistent. And additional research must be down before any particular method of warming can be used with confidence as to its effectiveness. Attention must be made as to the research design, better measurement of the dependent variables. This review may serve as a base.